Information processing device and information processing method

ABSTRACT

An information processing device includes an image acquirer that acquires a shot image of a user, a registered user information holder that holds face identification data of a registered user, a face recognition section that detects a face image of a registered user existing in the shot image by using face identification data held in the registered user information holder, and an information processing section that executes information processing based on a detection result by the face recognition section. The face identification data includes information on a face image of a user shot in advance and an after-processing image obtained by performing predetermined processing on the face image.

BACKGROUND

The present disclosure relates to an information processing device thatexecutes information processing by using a shot image and an informationprocessing method thereof.

In recent years, it is becoming general to equip a personal computer, agame machine, etc. with a camera and image the figure of a user to usethe taken image in various forms. For example, systems in which an imageof a user is transmitted to the other side as it is via a network, suchas television telephone and video chat, and systems in which the motionof a user is recognized by image analysis and the recognized motion isused as input information of a game or information processing have beenput into practical use (e.g. refer to WO 2007/050885 A2). Moreover, inrecent years, it is becoming possible to realize games and imageexpression giving a user a more feeling of being present in the realworld by detecting the motion of an object in a three-dimensional spaceincluding the depth direction with high accuracy.

SUMMARY

In the case of shooting a space where a wide variety of objects existand executing information processing with use of the shot image as inputdata, the accuracy of the information processing is more susceptible tothe shooting environment and so forth than in the case of operatingthrough buttons of an input device or a graphical user interface (GUI).Therefore, it is desired to realize a device that can execute stableinformation processing even when the environment changes. Furthermore,it is preferable that accurate associating is made with a small burdenon the user when the individual user is associated with the figure ofthe user in a shot image at the time of login or the like.

There is a need for the present disclosure to provide a technique thatallows keeping of stable accuracy with a small burden on the user ininformation processing with use of a shot image.

According to an embodiment of the present disclosure, there is providedan information processing device. This information processing deviceincludes an image acquirer configured to acquire a shot image of a user,a registered user information holder configured to hold faceidentification data of a registered user, a face recognition sectionconfigured to detect a face image of a registered user existing in theshot image by using face identification data held in the registered userinformation holder, and an information processing section configured toexecute information processing based on a detection result by the facerecognition section. The face identification data includes informationon a face image of a user shot in advance and an after-processing imageobtained by performing predetermined processing on the face image.

According to another embodiment of the present disclosure, there isprovided an information processing method. This information processingmethod includes acquiring a shot image of a user from a connectedimaging device, reading out face identification data of registered userstored in a storage device and detecting a face image of a registereduser existing in the shot image by using the face identification data,and executing information processing based on a result of the detection.The face identification data includes information on a face image of auser shot in advance and an after-processing image obtained byperforming predetermined processing on the face image.

What are obtained by translating arbitrary combinations of the aboveconstituent elements and expressions of the present disclosure amongmethod, device, system, recording medium, computer program, and so forthare also effective as embodiments of the present disclosure.

According to the embodiments of the present disclosure, informationprocessing using a shot image can be easily realized with high accuracy.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram showing an information processing system in anembodiment of the present disclosure;

FIG. 2 is a diagram showing the internal configuration of an informationprocessing device in the embodiment;

FIG. 3 is a diagram showing the functional block configuration of theinformation processing device in the embodiment;

FIG. 4 is a diagram showing one example of a space shot by a camera inthe embodiment;

FIG. 5 is a diagram showing the result of face identification by a faceauthentication section in the embodiment;

FIG. 6 is a diagram showing a login screen including face framesdisplayed on an output device in the embodiment;

FIG. 7 is a diagram showing the login screen in which a user puts theface in a face frame in the embodiment;

FIG. 8 is a flowchart showing the procedure of processing in which alogin controller of the information processing device in the embodimentdetermines whether or not to permit login by first-stage andsecond-stage face authentications;

FIG. 9 is a diagram schematically showing the procedure of generation offace identification data from a shot image by a data generator in theembodiment;

FIG. 10 is a flowchart showing the procedure of processing in which aface identification data registration section in the embodimentregisters the face identification data with determination of the timingwhen it should be registered;

FIG. 11 is a flowchart showing the procedure of the processing in whichthe face identification data registration section in the embodimentregisters the face identification data with determination of the timingwhen it should be registered;

FIG. 12 is a diagram showing one example of an image shot by the camerawhen login processing is executed with combining of face authenticationand marker detection in the embodiment;

FIG. 13 is a diagram showing the functional block configuration of theinformation processing device when the login processing is executed bythe face authentication and the marker detection in the embodiment;

FIG. 14 is a diagram showing an example of stereo images shot when astereo camera is used as the camera in the embodiment;

FIG. 15 is a diagram used to explain the relationship between disparityin stereo images and the position of a subject in the depth direction;

FIG. 16 is a flowchart showing procedure in which the informationprocessing device in the embodiment executes the login processing bycarrying out the face authentication and the marker detection with useof stereo images;

FIG. 17 is a diagram showing an example of a shot image in which markersare captured in the embodiment; and

FIG. 18 is a flowchart showing the procedure of processing ofidentifying a color that can be deemed as the marker in marker detectionprocessing in the embodiment.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

FIG. 1 shows an information processing system 1 according to anembodiment of the present disclosure. The information processing system1 includes an information processing device 10 as a user terminal and aserver 5. An access point (hereinafter, referred to as “AP”) 8 hasfunctions of a wireless access point and a router. The informationprocessing device 10 connects to the AP 8 in a wireless or wired mannerand communicably connects to the server 5 on a network 3.

An auxiliary storage device 2 is a high-capacity storage device such asa hard disc drive (HDD) or a flash memory. It may be an external storagedevice that connects to the information processing device 10 by auniversal serial bus (USB) or the like or may be a built-in storagedevice. An output device 4 may be a television having a display tooutput images and a speaker to output sounds or may be a computerdisplay. The output device 4 may be connected to the informationprocessing device 10 by a wiring cable or may be wirelessly connectedthereto.

The information processing device 10 connects to an input device 6operated by a user in a wireless or wired manner and the input device 6outputs an operation signal indicating an operation result by the userto the information processing device 10. When accepting the operationsignal from the input device 6, the information processing device 10reflects it in processing of an operating system (OS, i.e. systemsoftware) or an application and makes the processing result be outputfrom the output device 4. The input device 6 has plural input parts suchas plural push operation buttons, analog sticks with which an analogamount can be input, and pivotal buttons.

When accepting the operation signal from the input device 6, theinformation processing device 10 reflects it in processing of anapplication and makes the processing result be output from the outputdevice 4. In the information processing system 1, the informationprocessing device 10 is a game device that executes a game and each ofthe input devices 6 a and 6 b (hereinafter, often referred to as theinput device 6 generically) is an apparatus, such as a game controller,to provide the operation signal of a user to the information processingdevice 10. The input device 6 may be an input interface such as akeyboard and a mouse. A camera 7 as an imaging device is provided nearthe output device 4 and images a space around the output device 4.Although an example in which the camera 7 is attached to an upper partof the output device 4 is shown in FIG. 1, it may be disposed at a sidepart of the output device 4. In any case, the camera 7 is disposed at aposition at which it can image a user located in front of the outputdevice 4. The camera 7 may be a stereo camera.

The server 5 provides network services to users of the informationprocessing system 1. The server 5 manages network accounts to identifythe respective users and each user signs in the network servicesprovided by the server 5 by using the network account. By signing in thenetwork services from the information processing device 10, the user canregister, in the server 5, save data of a game and trophies as virtualprizes won in game play.

In FIG. 1, a situation in which two users A and B are operating theinput devices 6 a and 6 b as game controllers is shown. The users A andB operate the input devices 6 a and 6 b, respectively, to input apasscode for login. After being authenticated by the informationprocessing device 10, they log in to the OS of the informationprocessing device 10 and thereby can enjoy an application such as agame.

In recent years, a game in which the motion of a user is reflected inthe motion of a game character has also appeared. In a game utilizinggesture of a user, the user does not need to hold the input device 6 andcan intuitively move a character. In such a game, because the user doesnot use the input device 6 in the first place, it is preferable thatuser authentication is executed without use of the input device 6 alsowhen the user logs in to the OS of the information processing device 10.It is meaningful in the information processing system 1 that the usercan log in through simple user authentication irrespective of the kindof game to be played by the user after the login.

Therefore, in the information processing system 1 of the presentembodiment, a technique by which user authentication can be easilyexecuted by using a taken image by the camera 7 is provided.

FIG. 2 shows the internal configuration of the information processingdevice 10. The information processing device 10 has a main power button20, a power-ON light emitting diode (LED) 21, a standby LED 22, a systemcontroller 24, a clock 26, a device controller 30, a media drive 32, aUSB module 34, a flash memory 36, a wireless communication module 38, awired communication module 40, a sub-system 50, and a main system 60.

The main system 60 includes a main central processing unit (CPU), amemory as a main storage device, a memory controller, a graphicsprocessing unit (GPU), and so forth. The GPU is used mainly forarithmetic processing of a game program. These functions may beconfigured as a system on a chip and formed on one chip. The main CPUhas functions to activate an OS and execute an application installed inthe auxiliary storage device 2 under an environment provided by the OS.

The sub-system 50 includes a sub-CPU, a memory as a main storage device,a memory controller, and so forth and does not include a GPU. The numberof circuit gates of the sub-CPU is smaller than the number of circuitgates of the main CPU and the operating power consumption of the sub-CPUis lower than that of the main CPU. The sub-CPU operates in a periodduring which the main CPU is in the standby state and its processingfunctions are limited in order to suppress the power consumption. Thesub-CPU and the memory may be formed on different chips.

The main power button 20 is an input part to which an operation inputfrom a user is made. It is provided on the front surface of a casing ofthe information processing device 10 and is operated to turn on or offpower supply to the main system 60 of the information processing device10. Hereinafter, that the main power supply is in an on-state means thatthe main system 60 is in the active state, and that the main powersupply is in an off-state means that the main system 60 is in thestandby state. The power-ON LED 21 is lit when the main power button 20is switched on and the standby LED 22 is lit when the main power button20 is switched off.

The system controller 24 detects pressing-down of the main power button20 by the user. If the main power button 20 is pressed down when themain power supply is in the off-state, the system controller 24 acquiresthe pressing-down operation as an “on-instruction.” On the other hand,if the main power button 20 is pressed down when the main power supplyis in the on-state, the system controller 24 acquires the pressing-downoperation as an “off-instruction.”

The main CPU has a function to execute game programs installed in theauxiliary storage device 2 and a read-only memory (ROM) medium 44whereas the sub-CPU does not have such a function. However, the sub-CPUhas a function to access the auxiliary storage device 2 and a functionto transmit and receive data to and from the server 5. The sub-CPU hasonly such limited processing functions and therefore can operate atrelatively low power consumption compared with the main-CPU. Thesefunctions of the sub-CPU are executed when the main-CPU is in thestandby state. Because the sub-system 50 is operating when the mainsystem 60 is in the standby state, the information processing device 10of the present embodiment keeps being in the sign-in state in thenetwork services provided by the server 5.

The clock 26 is a real-time clock. It generates present date-and-timeinformation and supplies it to the system controller 24, the sub-system50, and the main system 60.

The device controller 30 is a large-scale integrated circuit (LSI) thatcarries out exchange of information among devices like a southbridge. Asshown in the diagram, to the device controller 30, devices areconnected, such as the system controller 24, the media drive 32, the USBmodule 34, the flash memory 36, the wireless communication module 38,the wired communication module 40, the sub-system 50, and the mainsystem 60. The device controller 30 absorbs the differences in theelectrical characteristics and the data transfer rate among therespective devices and controls the timing of data transfer.

The media drive 32 is a drive device that drives the ROM medium 44 thatis loaded therein and in which application software such as a game andlicense information are recorded and reads out a program, data, and soforth from the ROM medium 44. The ROM medium 44 is a read-only recordingmedium such as an optical disc, a magneto-optical disc, or a Blu-raydisc.

The USB module 34 is a module that connects to an external apparatus bya USB cable. The USB module 34 may connect to the auxiliary storagedevice 2 and the camera 7 by USB cables. The flash memory 36 is anauxiliary storage device forming an internal storage. The wirelesscommunication module 38 wirelessly communicates with e.g. the inputdevice 6 based on a communication protocol such as the Bluetooth(registered trademark) protocol or the IEEE 802.11 protocol.

The wireless communication module 38 may be compatible with a thirdgeneration digital mobile phone system that complies with theInternational Mobile Telecommunication 2000 (IMT-2000) standard definedby the International Telecommunication Union (ITU) and furthermore maybe compatible with a digital mobile phone system of another generation.The wired communication module 40 communicates with an externalapparatus in a wired manner and connects to the network 3 via the AP 8for example.

In the information processing system 1 of the present embodiment, if theuser presses down the main power button 20 when the informationprocessing device 10 is in the power-off state, the informationprocessing device 10 turns on the main power supply to activate the OS(system software) and execute login processing for the user. In thislogin processing, the information processing device 10 functions as aface authentication system using an image taken by the camera 7. Theoperation of the information processing device 10 will be describedbelow.

FIG. 3 shows the functional block configuration of the informationprocessing device 10. The information processing device 10 has an inputacceptor 102, an image acquirer 104, a login controller 110, aregistered user information holder 130, and a face identification dataregistration section 150. The login controller 110 has a taken imagedisplay section 112, a face authentication section 114, a face frameprocessing section 116, and a login processing section 120. The faceidentification data registration section 150 has a data generator 152and a registration determiner 154.

The input acceptor 102 accepts operation information from a user and theimage acquirer 104 acquires a taken image obtained by imaging by thecamera 7 and stores it in a memory. The camera 7 shoots a spatial imageat a predetermined cycle. Specifically, it shoots one spatial image per1/30 seconds for example and provides the taken images to the imageacquirer 104. The camera 7 is so disposed that its optical axis isoriented in the front direction of the output device 4 and therefore thecamera 7 shoots a user who exists in front of the output device 4.

The respective elements described as functional blocks that executevarious kinds of processing in FIG. 3 and FIG. 13 to be described latercan be formed with circuit block, memory, and other LSIs in terms ofhardware and are implemented by a program loaded into the memory and soforth in terms of software. Therefore, it is understood by those skilledin the art that these functional blocks can be implemented in variousforms by only hardware or only software or a combination of them, andthey are not limited to any.

In the present embodiment, the functions of the taken image displaysection 112, the face frame processing section 116, and the faceidentification data registration section 150 are implemented by a faceauthentication application. The functions of the face authenticationsection 114 are implemented by a face recognition engine and areautomatically activated by the OS when the main power button 20 ispressed down. The face authentication application and the facerecognition engine may be configured as one application.

One of characteristics of the information processing device 10 of thepresent embodiment is that it assists simple login operation of theuser. To log in to the OS of the information processing device 10, theuser should acquire a user account in advance and register it in theinformation processing device 10. Hereinafter, the user who hasregistered the user account in the information processing device 10 willbe referred to as the “registered user.”

The registered user information holder 130 holds various pieces ofinformation relating to the registered user. Specifically, it holds faceidentification data, an online identification data (ID) (nickname on thenetwork) of the user, a login passcode, and so forth as registered userinformation in association with the user account. The faceidentification data is feature data of a face image of the registereduser but may be face image data itself.

The face identification data is data employed as a comparison target inface recognition processing by the face authentication section 114. Itis generated by the face identification data registration section 150 tobe stored in the registered user information holder 130 in accordancewith a face recognition algorithm employed by the face authenticationsection 114. For example, the face identification data may be dataobtained by extracting, as characteristics, the relative positions andsizes of parts of a face and the shapes of eye, nose, cheekbone, andjaw. Furthermore, the face identification data may be data extracted asdifference data from standard data of the face image. In addition, itmay be a statistic representing the distribution of the luminance vectorand so forth. What kind of face identification data is to be extractedis determined depending on the employed face recognition algorithm. Inthe present embodiment, the face authentication section 114 employs aknown face recognition algorithm.

First, description will be made about processing when a registered userlogs in to the OS of the information processing device 10 in the statein which the registered user information has been stored in theregistered user information holder 130. In this example, at least usersA and B exist. The online ID of the user A is “HANAKO” and the online IDof the user B is “SACHIKO.”

When the user presses down the main power button 20 of the informationprocessing device 10, the main power supply of the informationprocessing device 10 is turned on and the input acceptor 102 acceptsinformation on the pressing-down of the main power button 20 as a loginrequest from the user. When the input acceptor 102 accepts the loginrequest, the respective functions in the login controller 110 areimplemented. The login controller 110 has a function to determinewhether or not to permit login of the user based on the result of facerecognition of the user.

When the input acceptor 102 accepts the login request based on thepressing-down of the main power button 20, the taken image displaysection 112 reads out a taken image acquired by the image acquirer 104from the memory and displays it on the output device 4, which is adisplay. A live image shot by the camera 7 is thereby displayed on theoutput device 4, so that the user present in front of the output device4 is displayed on the output device 4.

FIG. 4 shows one example of the space shot by the camera 7. In this shotspace, three users exist. A rectangular frame surrounding the users inFIG. 4 expresses the imaging range of the camera 7. The imaging range ofthe camera 7 defines the range displayed on the output device 4 as thelive image but the live image may be part of the taken image. The faceauthentication section 114 extracts a part estimated to be a person'sface in the taken image and derives feature data of this part. The faceauthentication section 114 then compares the derived feature data withface identification data held in the registered user information holder130 and determines whether or not the extracted face is the face of aregistered user.

Specifically, the face authentication section 114 derives the degrees ofmatch between the feature data of the extracted face image of the userand the face identification data of all registered users held in theregistered user information holder 130. This degree of match isnumerically expressed. For example, the degree of match is derived inthe form of a score out of 100. If the degree of match of a registeredface image with the feature data surpasses 90, the face authenticationsection 114 determines that the imaged user is a registered user andidentifies which registered user the imaged user is.

If plural face identification data whose degree of match surpasses 90exist, the face authentication section 114 may determine that the imageduser is the registered user of the face identification data with whichthe best score is derived. If the face identification data whose degreeof match surpasses 90 does not exist as the result of derivation of thedegrees of match between the feature data of the face image of the userextracted from the taken image and the face identification data of allregistered users, the face authentication section 114 determines thatthe user included in the taken image is not the registered user. In thismanner, the face authentication section 114 detects a face image of aregistered user existing in the taken image by using the faceidentification data held in the registered user information holder 130.As this face identification technique, a known technique may be used. Inthe present embodiment, this processing is positioned as first-stageface authentication.

FIG. 5 shows the result of face identification by the faceauthentication section 114. Here, it is determined that the left user isthe user A and the right user is the user B and the middle user is not aregistered user. The face authentication section 114 sets a face region200 a indicating the position of the face of the user A (online ID:HANAKO) in the taken image and a face region 200 b indicating theposition of the face of the user B (online ID: SACHIKO) in the takenimage, and provides the face frame processing section 116 withinformation to identify the position coordinates of the face regions 200a and 200 b and the imaged registered users. Hereinafter, an examplewill be shown in which the position coordinates are expressed bytwo-dimensional coordinates when the taken image is displayed on thedisplay. However, the position coordinates may be coordinates defined ona video random access memory (VRAM). In any case, it is enough that thecoordinates of the face regions 200 a and 200 b (hereinafter, oftenreferred to as the face region 200 generically) and the coordinates offace frames to be described later are expressed on a common coordinatesystem.

Each face region 200 may be set as a rectangular region in contact withthe contour of the face in the taken image. Alternatively, it may be setas a rectangular region slightly wider than the facial contour. Here,the contour of the face means a contour including the head hair.However, the contour of the face may be set excluding the head hair ifthe head hair is not taken into consideration in face recognitionprocessing of the face authentication section 114 for example. The sizeand shape of the face region 200 are determined by the size and shape ofthe face of the user in the taken image. Therefore, the size and shapeof the face region 200 differ for each user. Furthermore, even for thesame user, the size and shape of the face region 200 change depending onthe distance from the camera 7.

The information that is provided from the face authentication section114 to the face frame processing section 116 and is to identify theregistered user may be the user account of the registered user or may bethe online ID. The face authentication section 114 provides the faceframe processing section 116 with the position coordinates of the faceregion 200 in association with the registered user identificationinformation.

Specifically, in the example shown in FIG. 5, the face authenticationsection 114 provides the face frame processing section 116 with acombination of the face region 200 a and the identification informationof the user A and a combination of the face region 200 b and theidentification information of the user B.

The face frame processing section 116 displays a face frame on theoutput device 4 for the registered user detected by the faceauthentication section 114. This face frame is displayed in order forthe registered user to move the face and dispose it in the face framewhen logging in. Therefore, the registered user is allowed to log in tothe information processing device 10 by putting the user's own face inthe face frame displayed on the output device 4.

FIG. 6 shows a login screen including face frames displayed on theoutput device 4. The face frame processing section 116 displays faceframes 210 a and 210 b (hereinafter, often referred to as the face frame210 generically) for registered users based on the information that isprovided from the face authentication section 114 and is to identify theposition coordinates of the face regions 200 a and 200 b and the imagedregistered users. In this example, the face frame processing section 116displays the face frame 210 a for the user A and displays the face frame210 b for the user B. At this time, the face frame processing section116 displays the online ID of the user A near the face frame 210 a anddisplays the online ID of the user B near the face frame 210 b. Thisallows the users A and B to come to know that the own face is properlyrecognized and prompts them to move the face into the face frames 210 aand 210 b.

If an online ID different from the own online ID is displayed near theface frame 210 displayed near the own face, the user can come to knowthat the face recognition is not properly carried out and therefore doesnot put the face in the face frame 210. Additional information, such asthe degree of match between the registered data of a registered user andthe shot face image, derived when this registered user is identified inthe first-stage face authentication, may be further displayed near theface frame 210. This makes it easier for the user to recognize whetheror not the face recognition is properly carried out.

Because the middle user is not a registered user, the face frame 210 isnot displayed. However, for the user who is not a registered user, anindication showing that the user is not determined as a registered usermay be displayed near a region estimated to be a person's face. Forexample, displaying character information such as “unknown” or“unregistered” allows the user to find that the user is unregistered orthat the feature data of the already-registered face image is improper.However, it is also possible that authentication is temporarilyunsuccessful due to the orientation of the user's face or any blockingobject. Therefore, a predetermined rule may be set, such as a rule thatsuch information is displayed if the unsuccessful state continues for apredetermined time or longer.

The face frame processing section 116 gives an ID to each of the faceframes 210 and provides the face authentication section 114 with faceframe IDs, the position coordinates of the face frames 210, and theidentification information of the users for which the face frames 210are displayed. The position coordinates of the face frame 210 providedto the face authentication section 114 by the face frame processingsection 116 may be the position coordinates of the face frame 210 itselfor may be the coordinates of a rectangle circumscribed about the faceframe 210. Hereinafter, the position coordinates of the face frame 210itself and the position coordinates of a rectangle circumscribed aboutthe face frame 210 will be referred to as the position coordinates ofthe face frame collectively. The position coordinates of the face frameare used to detect a face image of the user in the face authenticationsection 114.

For example, the face frame processing section 116 sets “ID1” as theface frame ID of the face frame 210 a and sets “ID2” as the face frameID of the face frame 210 b. The face frame processing section 116provides the face authentication section 114 with a combination of“ID1,” the position coordinates of the face frame 210 a, and theidentification information of the user A and a combination of “ID2,” theposition coordinates of the face frame 210 b, and the identificationinformation of the user B. Furthermore, the face frame processingsection 116 provides the login processing section 120 with the faceframe IDs and the identification information of the users for which theface frames 210 are displayed. Therefore, in this case, the face frameprocessing section 116 provides the login processing section 120 with acombination of “ID1” and the identification information of the user Aand a combination of “ID2” and the identification information of theuser B.

FIG. 7 shows a login screen in which a user has put the face in a faceframe. Here, a state is shown in which the user A has moved the face andbody in such a manner that the face enters the face frame 210 adisplayed on the output device 4. The face authentication section 114monitors whether a person's face is put in the face frame 210. If a faceis put therein, the face authentication section 114 determines whetherthe face put in the face frame 210 is the face of the registered user byusing face identification data held in the registered user informationholder 130.

The face authentication section 114 can monitor whether a person's faceis put in the face frame 210 based on the position coordinates of theface frame 210 provided from the face frame processing section 116. Theface recognition algorithm is as described above. When estimating that aperson's face is included in the face frame 210, the face authenticationsection 114 derives the feature data of this part and compares thefeature data with face identification data held in the registered userinformation holder 130 to determine that the extracted face is the faceof the registered user.

The face authentication section 114 has been notified of the combinationof the face frame ID, the position coordinates of the face frame 210,and the identification information of the user for which the face frame210 is displayed from the face frame processing section 116, andcompares the feature data of the face image of the person included inthe face frame 210 with the face identification data of the user forwhich the face frame 210 is displayed. Because having been notified ofthe user that should be included in the face frame 210 in advance, theface authentication section 114 does not need to compare the featuredata of the face included in the face frame 210 with the faceidentification data of all registered users and thus can efficientlyexecute the face recognition processing. The face authentication section114 may temporarily store the face image of the user extracted from thetaken image in the first-stage face authentication or the feature datathereof, described with FIG. 5, and include also it in the comparisontargets. Details will be described later.

The face authentication section 114 may determine that the face of theregistered user is put in the face frame 210 by detecting that the faceof the registered user has been put in the face frame 210 for apredetermined time (e.g. several seconds). As a result, in the exampleof FIG. 7, the face authentication section 114 determines that the facethat has entered the face frame 210 a is the face of the user A. In thepresent embodiment, this processing is positioned as second-stage faceauthentication.

Through the first-stage and second-stage face authentications, the userauthentication at the time of login ends. The action of putting a facein the face frame 210 by a user is made based on the user's intention tolog in. When the user does not desire to log in, the user does not needto put the face in the face frame 210. As above, in the presentembodiment, the registered user who will possibly log in is detected bythe first-stage face authentication and the registered user having anintention to log in is detected by the second-stage face authentication.The registered user is authenticated by only carrying out simpleoperation of putting the face in the face frame 210. Thus, the workingburden on the user at the time of login can be made very small.

When detecting that the face of the user A has entered the face frame210 a, the face authentication section 114 notifies the login processingsection 120 of the face frame ID to identify the face frame 210 a andthe user identification information to identify the user A. As alreadydescribed, the login processing section 120 has been notified of theface frame IDs and the identification information of the users for whichthe face frames 210 are displayed from the face frame processing section116 in advance. When being notified of the face frame ID and the useridentification information from the face authentication section 114, thelogin processing section 120 extracts the user identificationinformation associated with the face frame ID notified from the faceframe processing section 116 and determines the match between the piecesof user identification information. Here, corresponding to the faceframe ID of ID1, the identification information of the user A isnotified as both of the pieces of identification information from theface authentication section 114 and the face frame processing section116. Therefore, the login processing section 120 recognizes that theface of the user A is detected in the face frame 210 a displayed for theuser A. Due to this, the login processing section 120 allows the user Ato log in to the information processing device 10.

As described above, in the present embodiment, the login controller 110causes a registered user to log in after carrying out the userauthentication by face authentications of two stages. For example, aftera person's face is detected in the first shot image and whether or notthe person with the detected face is a registered user is determined inthe first-stage face authentication processing, face authenticationprocessing does not need to be executed unless a new user is shot. Inthis case, the detected person's face is subjected to trackingprocessing in the shot image and the position coordinates of the faceimage in the shot image are constantly provided to the face frameprocessing section 116. It is also possible to employ a configuration inwhich face authentication is executed at a predetermined cycle and adetected person's face is subjected to tracking processing in the timezone during which face authentication is not executed.

The first-stage face authentication and the second-stage faceauthentication may be concurrently executed at different cycles. Forexample, the first-stage face authentication and the second-stage faceauthentication are concurrently operated at a cycle of one second and acycle of 1/60 seconds, respectively. Due to this, particularly when alarge number of users exist at a time, the speed of the login processingcan be enhanced compared to the case in which the face authenticationsof the two stages are executed one person by one person. By setting theoperating cycle of the first-stage face authentication long and settingthe operating cycle of the second-stage face authentication short asdescribed above, transition from the first stage to the second stage canbe rapidly made with a suppressed processing burden.

After login of one registered user through the second-stage faceauthentication processing, if a registered user who has not yet loggedin is being shot, the login screen may continue to be displayed untilthis registered user logs in. In this case, it is preferable for theface frame processing section 116 to erase the face frame 210 displayedfor the user who has logged in from the output device 4. If there is alimit that only one registered user is allowed to log in through thisface authentication, transition to the home screen provided by the OS ofthe information processing device 10 or the like may be made after loginof one registered user.

If the face authentication section 114 cannot detect a face in the faceframe 210 for a predetermined time after the face frame 210 is displayedin the login screen, the login processing by face authentication may endand transition to login processing by use of the input device 6 may bemade. Furthermore, if the user does not desire the login processing byface authentication, the login processing by face authentication may beended by using the input device 6 for example and transition to loginprocessing by use of the input device 6 may be made.

Next, description will be made about the operation of the informationprocessing device 10 in the case of using the face image acquired in thefirst-stage face authentication for the second-stage face authenticationas described above. FIG. 8 is a flowchart showing the procedure ofprocessing in which mainly the login controller 110 of the informationprocessing device 10 determines whether or not to permit login by thefirst-stage and second-stage face authentications. First, the faceauthentication section 114 extracts a part estimated to be a person'sface in a shot image as described above and makes a comparison with faceidentification data held in the registered user information holder 130to thereby determine that the extracted face is the face of a registereduser (S10).

During the period in which a face is not detected or the detected faceis not the face of a registered user, i.e. the first-stage faceauthentication is unsuccessful, the face detection and the determinationprocessing are repeated at a predetermined time interval (N of S10). Ifit is determined that the detected face is the face of a registered userand the first-stage face authentication succeeds (Y of S10), the faceauthentication section 114 temporarily stores, in an internal memory orthe like (not shown), the image of the face region extracted from theshot image at this time or the feature data thereof in association withthe identification information of the corresponding registered user(S12). The face authentication section 114 notifies the face frameprocessing section 116 of the position coordinates of the face regionand the identification information of the registered user as describedabove.

This causes the face frame processing section 116 to display face frameand online ID on the output device 4 as shown in FIG. 6 (S14). Alongwith this, the face frame processing section 116 notifies the faceauthentication section 114 of the face frame ID, the positioncoordinates of the face frame, and the identification information of thecorresponding registered user. In response to this, the faceauthentication section 114 performs monitoring until a person's faceenters the face frame or a predetermined range including the peripherythereof (N of S16). If it can be detected that a person's face hasentered the relevant range (Y of S16), the face authentication section114 derives the feature data of this face region. The faceauthentication section 114 makes a double determination by comparing thederived feature data with both of face identification data held in theregistered user information holder 130 (hereinafter, often referred toas “long-term stored data”) and the feature data of the face regionextracted from the shot image in the first-stage face authentication tobe temporarily stored in S12 (hereinafter, often referred to as“short-term stored data”) (S18).

Specifically, first the feature data of the face in the face frame iscompared with the long-term stored data. If it is determined that thesedata do not match, comparison with the short-term stored data is triednext. If it is determined that both correspond to the face of the sameperson through this comparison, the face authentication section 114concludes that the face in the face frame is the face of the registereduser identified by the first-stage face authentication. That is, theface authentication section 114 changes the failure of theauthentication with the long-term stored data to success.

For example, if the success rate of the authentication with thelong-term stored data is 80%, executing the same authenticationprocessing twice decreases the success rate of the authentication toabout 60%. If tilting the face changes e.g. the roundness of a cheek,possibly the success rate further decreases. In this case, possibly asituation occurs in which the second-stage face authentication does notsucceed and the user cannot log in although it is authenticated that adetected face is the own face in the first-stage face authentication, sothat the user will be given stress. With the above-describedconfiguration, the success rate of the authentication can be enhanced byusing the image shot immediately before the second-stage faceauthentication.

In the present embodiment, the main meaning of the second-stage faceauthentication is checking whether or not a user has an intention to login and the detection itself of the registered user is assumed mainly bythe first-stage face authentication. By doubly executing thesecond-stage face authentication as described above to loosen theauthentication criterion, authentication having consistency with such adifference in the meaning can be realized. Furthermore, by using theimage obtained at the time of the first-stage face authentication, theabove-described effects can be achieved without increasing labor imposedon the user.

The order of the authentication with the long-term stored data and theauthentication with the short-term stored data and the rule ofderivation of the determination result are not limited to theabove-described ones. Both authentications may be simultaneously carriedout and scores representing the results of them may be integrated.Alternatively, the authentication with the short-term stored data may becarried out first. In the above description, to loosen theauthentication criterion to enhance the success rate of theauthentication, the union of success events of both is determined as thefinal success event. However, depending on the purpose, theauthentication criterion may be made stricter. That is, the intersectionof success events of the authentication with the long-term stored dataand the authentication with the short-term stored data may be deemed asthe final success event. In any case, multifaceted authentication isenabled by using two kinds of face identification data different in theacquisition timing.

Next, description will be made about processing in which the faceidentification data registration section 150 stores face identificationdata (above-described “long-term stored data”) in the registered userinformation holder 130. At a stage where the face identification datashould be stored, the data generator 152 of the face identification dataregistration section 150 reads out data of a shot image acquired by theimage acquirer 104 from the memory and extracts a part estimated to be aperson's face in this image to derive feature data.

The stage where the face identification data should be stored istypically a case in which a user newly desires user registration. Inthis case, when accepting a request for start of user registration fromthe user via the input device 6, the input acceptor 102 notifies theface identification data registration section 150 of this. Meanwhile,the camera 7 starts shooting of the face of this user and the faceidentification data registration section 150 reads out data of therelevant image acquired by the image acquirer 104 from the memory. Theface identification data registration section 150 then extracts the faceregion and derives feature data as described above. In addition, itstores the derived data in the registered user information holder 130 inassociation with a new online ID that is input by the user and acceptedby the input acceptor 102 and user identification information such as anaccount given by the device.

The face identification data stored here differs depending on the facerecognition algorithm employed by the face authentication section 114 asdescribed above and may be either feature data or face image dataitself. As one of face recognition algorithms, there is a method inwhich the degree of match is calculated based on a difference imagebetween a shot face image and a face image registered in advance and thedistance from an eigenspace of a difference image group acquired inadvance (refer to e.g. Japanese Patent Laid-open No. 2002-157596). Notonly in this technique but in authentication based on a pixel value set,such as authentication in which block matching is performed between animage shot at the time of the authentication and a registered image andauthentication in which probability density is obtained based on theluminance distribution vector of an image with a statistic such as acovariance matrix, the authentication accuracy is susceptible to theface image as the source of the registered data.

For example, possibly the overall luminance and the angle of lightshining on a face greatly differ between an image shot under naturallight incident from a window and an image shot under indoor illuminationat night. When these images are compared, the accuracy of derivation ofthe degree of match and hence the authentication accuracy tends to below compared with when images shot under the same illuminationenvironment are compared. Such a change in the illumination environmentis caused due to various factors such as time zone, weather, whether acurtain is opened or closed, and which illumination lamp is lit. Theauthentication accuracy possibly changes due to change in not only theillumination environment but various conditions such as the orientationof the face, whether glasses and hat are worn, hair length andhairstyle, whether the face is shaved, and whether before or aftertanning.

Therefore, in the case of statistical authentication, it is preferablethat a statistic is calculated from images in as many states as possibleat the learning stage of the statistical authentication. In the case ofperforming block matching with each registered image, it is preferablethat registered images in as many states as possible are stored.However, actually there is a limit to creation of such states by theuser oneself. Therefore, the data generator 152 performs a predeterminedprocessing treatment for a face image of the user shot at the time ofregistration to thereby enhance the authentication accuracy with a smallburden on the user.

FIG. 9 schematically shows the procedure of generation of faceidentification data from a shot image by the data generator 152. First,at a stage where face identification data should be stored, the datagenerator 152 extracts an image 300 representing a face region from animage shot by the camera 7. This processing may be similar to theprocessing of face detection executed by the face authentication section114. The data generator 152 generates after-processing images 302 a, 302b, and 302 c by performing predetermined processing for the image 300 ofthis face region. The contents of the processing performed here are setinside the data generator 152 in advance.

In the case of FIG. 9, the after-processing image 302 a is an image of asmiley face obtained by applying a predetermined distortion filter tothe eye region in the original image 300. It may be created by morphingwith a smiley face image of an average face. The after-processing image302 b is an image synthesized by superimposing an image of glasses onthe original image 300. The after-processing image 302 c is an image inwhich the luminance is partially lowered in such a manner that the righthalf of the face is shaded. In this case, further, the incident angle ofpredetermined light may be assumed and a range in which a shadow is mademay be calculated as a region in which the luminance is lowered inconsideration of also the concavity and convexity of the face, such asthe nose. At this time, the incident angle of light may be changed togive the shadow in plural patterns. Instead of merely giving the shadow,the luminance of a part illuminated with light may be increased.

Other examples of the image processing will be as follows: the luminanceis totally changed; the orientation (any of the rotational angles in theyaw/pitch/roll directions or a combination thereof) of a face is changedby affine transformation; a beard image with a mustache, whisker, jawbeard, or the like is combined; a hair image of any of varioushairstyles is combined; an image of an accessory such as a hat or maskis combined; a region of a front hair or beard is deleted and the colorof the region is turned to a flesh color; the shape of parts of theface, such as cheek, mouth, and eyebrow, is deformed by morphing or thelike; and the color of the skin is darkened or lightened.

Moreover, shot images of a face in plural orientations (any of therotational angles in the yaw/pitch/roll directions or a combinationthereof) may be acquired by shooting a user from plural directions bythe camera 7 and a face image in an intermediate orientation of theseorientations may be generated as an after-processing image. For example,from shot images of a face oriented in the front and lateral directions,an after-processing image of the face oriented in an intermediatedirection of these directions, i.e. in an oblique direction, isgenerated. The “intermediate direction” may be an arbitrary directionamong the plural directions in which the shooting is performed and thenumber thereof is also not limited. To the processing, a generaltechnique to generate an interpolated image from plural images may beapplied.

Besides, any of face processing methods based on general imageprocessing techniques may be employed. In the case of individuallymaking comparison with each registered image, one after-processing imagemay be created by combining plural kinds of processing. The datagenerator 152 generates face identification data 304 by using the image300 of the original face region and the after-processing images 302 a,302 b, and 302 c and stores it in the registered user information holder130. As described above, depending on the algorithm used forauthentication, data of each image or part thereof may be individuallystored as it is or data obtained by subjecting all images to statisticalprocessing may be stored. Due to this, for one registered user,authentication in consideration of also many assumed states can berealized and stable login is enabled without labor of reregistration inwhatever state.

In the above description, a case in which a user requests newregistration is exemplified as a stage where face identification datashould be stored. In the present embodiment, further other opportunitiesare set to increase the frequency of update of the face identificationdata and keep the accuracy of authentication processing. For thispurpose, the registration determiner 154 of the face identification dataregistration section 150 determines the timing when face identificationdata is newly stored (registered). Specifically, the registrationdeterminer 154 deems timing when a user makes a request forregistration, such as new registration or additional registration, asthe timing of registration of face identification data. Furthermore,when the first-stage authentication succeeds and when the second-stageauthentication succeeds, if a face image shot and detected at the timingsatisfies a predetermined condition, the registration determiner 154determines this timing as the timing of registration of this face image.

When determining that the present timing is the timing of registration,the registration determiner 154 notifies the data generator 152 of this.This causes the data generator 152 to store generated faceidentification data in the registered user information holder 130. Thedata generator 152 may always perform the above-described imageprocessing at all timings or may skip it depending on the timing. Forexample, when determining whether or not to register face identificationdata based on a face image detected at the time of authentication, theregistration determiner 154 may simultaneously determine also whether ornot to perform image processing and notify the data generator 152 of thedetermination result.

FIGS. 10 and 11 are flowcharts showing the procedure of processing inwhich the face identification data registration section 150 registersface identification data with determination of the timing when it shouldbe registered. Referring first to FIG. 10, when a user makes an input torequest new registration (Y of S20), the data generator 152 reads outdata of a shot image acquired by the image acquirer 104 and extracts animage of a face region as described above. The data generator 152 thengenerates face identification data by arbitrarily performing processingand so forth. Because the registration determiner 154 determines alltimings of a request for new registration as the timing when faceidentification data should be registered, the data generator 152 storesthe generated data in the registered user information holder 130 (S22).

If a registered user who has already finished new registration makes aninput to request additional registration of the user's own face onanother opportunity (N of S20, Y of S24), the camera 7 starts shootingof this user and the data generator 152 reads out data of a shot imageacquired by the image acquirer 104. The data generator 152 then extractsa face region and derives feature data of this region (S26). Theadditional registration possibly occurs when the user oneself becomesaware of the necessity for registration due to the elapse of a certainamount of time from the previous registration or change in the state ofthe user for example.

The registration determiner 154 reads out already-registered faceidentification data from the registered user information holder 130based on an online ID input by the user or the like and compares it withthe feature data derived by the data generator 152 (S28). The generationof feature data and the comparison with face identification data arebasically the same as the processing executed by the face authenticationsection 114 at the time of authentication processing. Therefore, it isalso possible to employ a configuration in which these kinds ofprocessing are entrusted to the face authentication section 114 and thedata generator 152 only acquires feature data and the registrationdeterminer 154 only acquires the comparison result thereof.

When the comparison result satisfies a first condition set in advance,the registration determiner 154 determines that the present timing isthe timing when the face image shot at this time should be registeredand notifies the data generator 152 of this (Y of S28). This causes thedata generator 152 to add the feature data generated in S26 to the faceidentification data associated with the corresponding user in theregistered user information holder 130 (S30). The first condition is setabout the degree of match between the feature data of the face imageextracted from the shot image and the already-registered faceidentification data of the corresponding user. For example, if thedegree of match is too low, there is a possibility of masquerading by adifferent person or erroneous input of the online ID and therefore newregistration is not carried out.

Conversely, if the degree of match is too high, registering similar dataagain will not contribute to the authentication accuracy at all andtherefore new registration is not carried out. Therefore, for the degreeS of match (0≦S≦100), a condition of e.g. s1≦S≦s1′ (s1<s1′) is set asthe first condition. However, this does not intend to limit the firstcondition to this format and only either one of the lower limit s1 andthe upper limit s1′ may be set for the degree S of match. If thecomparison result does not satisfy the first condition in S28, e.g. animage for notifying the user of this is displayed and the processingends without registration (N of S28).

FIG. 11 shows a processing procedure when new face identification datais automatically registered according to need by utilizing the timing ofactual login by a user who has already finished registration. In thiscase, the face identification data registration section 150 acquires thenecessary data from the login controller 110. The face identificationdata registration section 150 then determines whether or not newregistration should be carried out based on it and thereafter executesregistration processing.

First, if the first-stage face authentication succeeds (Y of S40), theface authentication section 114 of the login controller 110 supplies theface identification data registration section 150 with the feature dataof the face image extracted from the shot image at the time of this faceauthentication, the online ID of the registered user identified aboutit, the degree of match with the face identification data of thisregistered user, derived as the authentication result (S42). At thistime, in addition to the degree of match with the face identificationdata of the identified registered user, the degree of match with theface identification data of other users may also be supplied.

The registration determiner 154 determines whether or not this degree ofmatch satisfies a second condition set in advance (S44). If the secondcondition is satisfied, the registration determiner 154 determines thatthe present timing is the timing when the face image used for theauthentication in S40 should be registered and notifies the datagenerator 152 of this (Y of S44). This causes the data generator 152 toadd the feature data acquired in S42 to the face identification dataassociated with the corresponding user in the registered userinformation holder 130 (S46). The registration is not carried out if thesecond condition is not satisfied (N of S44).

Subsequently, if the second-stage face authentication succeeds (Y ofS48), the face authentication section 114 of the login controller 110supplies the face identification data registration section 150 with thefeature data of the face image in a face frame, the online ID of theregistered user identified about it, and the degree of match with faceidentification data (S50). At this time, in addition to the degree ofmatch with the face identification data of the identified registereduser, the degree of match with the face identification data of otherusers may also be supplied. The registration determiner 154 thendetermines whether or not this degree of match satisfies a thirdcondition set in advance (S52).

If the third condition is satisfied, the registration determiner 154determines that the present timing is the timing when the face imageused for the authentication in S48 should be registered and notifies thedata generator 152 of this (Y of S52). This causes the data generator152 to add the feature data acquired in S50 to the face identificationdata associated with the corresponding user in the registered userinformation holder 130 (S54). The registration is not carried out if thethird condition is not satisfied (N of S52). Naturally, the registrationis not carried out also when the first-stage or second-stage faceauthentication is unsuccessful (N of S40, N of S48).

The second condition used in S44 and the third condition used in S52 areset based on a policy similar to that on the first condition describedwith reference to FIG. 10 qualitatively. For example, for the degree Sof match with the face identification data of the registered useridentified because of e.g. the highest degree of match in the faceauthentication by the face authentication section 114, a condition ofe.g. s2≦S≦s2′ (s2<s2′) is set as the second condition and a condition ofe.g. s3≦S≦s3′ (s3<s3′) is set as the third condition. Moreover, for thedegree Mi of match with the face identification data of another user i(0<i≦n, n is the number of other users), a condition of e.g. Mi≦m2 isset as the second condition and a condition of e.g. Mi≦m3 is set as thethird condition.

When all conditions about the degrees S and Mi of match are satisfied,it is determined that the second and third conditions are satisfied.When the degree Mi of match with the face identification data of anotheruser is high, the face image will be similar also to the face of anotheruser at a certain level, while being similar to the face of theidentified user. Registering such an image easily causes confusion withthis another user in authentication. Therefore, such an image isexcluded from the registration subject by setting the upper limit to Mi.Preferably, the thresholds about the degree S of match with the faceidentification data of the user oneself are set independently of eachother regarding the first, second, and third conditions. The thresholdsabout the degree Mi of match with the face identification data ofanother user are also set independently of each other regarding thesecond and third conditions.

For example, when a user desires additional registration for oneself,face identification data as the comparison target is decided based on anonline ID input by the user and therefore the possibility that thecorrespondence between a shot face image and the face identificationdata is accurate is higher than at other timings. Furthermore, it ispreferable that the probability of registration is high also because theuser oneself requests the registration. Therefore, the thresholds are soset as to provide the widest range as the range of the degree S of matchin which the present timing is determined as the timing when theregistration should be carried out.

The registration at the time of the first-stage face authentication andthe registration at the time of the second-stage face authentication areboth automatically carried out by the device. However, the accuracy ofthe correspondence between a face image and a user in the second-stageface authentication is higher than that in the first stage because theuser oneself expresses that the correspondence between the face imageand the online ID is correct by putting the face in a face frame.Therefore, the ranges of the degrees S and Mi of match in which thepresent timing is determined as the timing when registration should becarried out are set wider than those of the first stage. By such aconfiguration, opportunities to register face identification data can beincreased as much as possible with a small burden on the user andauthentication can be carried out based on the latest informationconsistently. As a result, it is possible to realize authenticationprocessing robust against long-term changes such as change in a face dueto growth and aging in addition to condition changes in a comparativelyshort period, such as change in the above-described illuminationenvironment.

By changing the condition for deciding whether or not to carry outregistration according to the intention of the user, the accuracy ofinput information, and so forth, the frequency of erroneous registrationand useless registration can be suppressed. If data of face images ordata of part thereof is stored as face identification data, part of thealready-stored face identification data of the corresponding user may bedeleted concurrently with new registration of face identification data.For example, the following data are preferentially deleted: the oldestdata; data that had a lower degree of match than other data in thehistory of past authentication processing although being data of thesame user; and data older than other data in the timing when the datawas used for success in authentication (it was determined that thedegree of match with a shot image was higher than a threshold or thedegree of match was the highest when the authentication succeeded).

In the latter case, every time the corresponding user logs in, thedegrees of match calculated about the respective face identificationdata in the authentication of the login are stored and the faceidentification data are deleted in increasing order of the average ofthe history of the degree of match. This can save the capacity of theregistered user information holder 130. In addition, if plural faceidentification data of the same user are each compared with a shot imagein e.g. authentication through block matching, the comparison target canbe decreased to reduce the burden of the authentication processing andthe time it takes to execute the processing.

As above, in the case of individually storing face identification dataevery time registration is carried out and comparing each of the storeddata with a shot image, an upper limit may be set on the number of faceidentification data stored in the registered user information holder 130and, if data has been registered to this upper limit, any of thealready-stored data may be overwritten when new data is registered. Inthis case, the following scheme may be further employed.

Specifically, face identification data are stored in the registered userinformation holder 130 in such a manner that face identification dataregistered based on the intention of the user as shown in FIG. 10 areclassified into a first group and face identification data automaticallyregistered by the device as shown in FIG. 11 are classified into asecond group. Furthermore, for each of these groups, an upper limit isset on the number of data that can be stored. In registration of dataexceeding the upper limit, already-stored data of the first group isoverwritten if the new data is data of the first group andalready-stored data of the second group is overwritten if the new datais data of the second group.

This can prevent the occurrence of an inconvenience that the faceidentification data registered based on the intention of the user areall overwritten with face identification data automatically registeredby the device and the authentication accuracy is lowered. Moreover, itis also possible to employ a configuration in which a counter to countthe number of times of use for success in authentication for each ofalready-registered face identification data is provided and the datawith the smallest number of times of use is overwritten when new data isregistered. However, for just-registered data, the number of times ofuse for success in authentication is small naturally. Therefore, aviewpoint relating to time may be taken into consideration.Specifically, for example the number of times of use may be weighteddepending on the elapsed time from registration. Furthermore, the faceidentification data selected as a candidate for overwriting may befurther compared with the data that should be newly registered and thenew registration may be cancelled if the degree of match is higher thana predetermined threshold. This can prevent the occurrence of aninconvenience that the number of times of use for success inauthentication returns to 0 although the newly registered data issimilar to the overwritten data and this newly registered data is easilyselected as the overwriting target.

In any case, qualitatively it is preferable that face identificationdata used for success in authentication many times is prevented frombeing overwritten and a wide variety of data obtained under differentillumination conditions and so forth are left as much as possible. Itwill be understood by those skilled in the art that variousmodifications are possible besides the above-described ones as methodsfor this purpose.

In the above, the login method based on face authentications of twostages without use of an input device is described. Next, aconsideration will be made about a case in which an input device is usedin processing after login, specifically a case in which the motion of auser is detected by shooting a marker provided on the input device and agame is made to progress or information processing is executed accordingto this. In the case of detecting the motion of plural users in such amode, the motion of each user can be identified based on the color ofthe marker if the colors of the markers of the input devices held by therespective users are made different from each other. Therefore, thecolor of the marker of the input device is associated with the user whoholds this input device at the time of login.

FIG. 12 shows one example of an image shot by the camera 7 when loginprocessing is executed with combining of face authentication and markerdetection. One user is captured in a shot image 400 and this user holdsthe input device 6 a. The input device 6 a has a marker 402 as shown inan enlarged view (input device 6 b) on the right side of FIG. 12. Themarker 402 is formed of a light emitting diode that emits light with apredetermined color for example. However, the marker 402 does not needto emit light and the form thereof is not limited as long as it is anobject that has known color, shape, and size and can serve as adetection target. It is also possible to stick a figure drawn on aplane, such as a two-dimensional bar code, to the input device 6 a ordraw a figure directly on the input device 6 a.

The marker 402 is oriented toward the camera 7 when the user grasps leftand right grip parts of the input device 6 a with both hands and facesthe camera 7 as shown in the diagram. The input device 6 a may haveoperation units such as various kinds of operation buttons and joysticksbesides the marker 402 although not shown in the diagram. The shape ofthe input device is not limited to that shown in the diagram. In thisexample, first, by the above-described first-stage face authentication,a registered user is identified based on feature data of a face image byusing a face region 404 in the shot image 400. Furthermore, a region 406of the image of the marker 402 is detected. Its color is then associatedwith the identified registered user to be utilized for later-stageinformation processing.

A rule that the user holds the input device 6 a at a predeterminedposition such as a position in front of the chest at the time of loginis set in advance so that the correspondence between the face and themarker may be understood based on the relative positions of the faceregion 404 in the shot image 400 and the region 406 of the image of themarker corresponding to it. For example, the online ID of the registereduser identified by face authentication is displayed near the face region404 and the user who has confirmed that it is the own online ID holdsthe input device 6 a in front of the own chest. Due to this, theinformation processing device 10 detects the marker in the region 406 ofthe image of the marker and associates its color with the registereduser. The position at which the input device 6 a is held is not limitedto one in front of the chest and may be under the jaw, above the head,or beside a ear for example as long as the position is set in advanceand is recognized by the user.

FIG. 13 shows the functional block configuration of the informationprocessing device 10 when login processing is executed by faceauthentication and marker detection. The same functional blocks as thoseshown in FIG. 3 are given the same numerals and description thereof isomitted. It is also possible to employ a configuration in which allfunctional blocks included in the login controller 110 shown in FIG. 3are included in a login controller 160 shown in FIG. 13 and a user canselect which login mode is used via the input device 6.

The information processing device 10 includes the input acceptor 102,the image acquirer 104, the login controller 160, and a registered userinformation holder 168. The information processing device 10 may furtherinclude the face identification data registration section 150 shown inFIG. 3. The login controller 160 has the taken image display section112, the face authentication section 114, a marker authenticationsection 162, a distance identifier 164, and a login processing section166.

The input acceptor 102, the image acquirer 104, and the taken imagedisplay section 112 and the face authentication section 114 in the logincontroller 160 have the same functions as those of the respectivefunctional blocks shown in FIG. 3. However, the face authenticationsection 114 carries out only the first-stage authentication, which iscomposed of detection of a face region included in a shot image andidentification of a registered user, and provides the markerauthentication section 162 with information on the face region and theidentified registered user. The registered user information holder 168holds identification information such as the online ID of the user andface identification data in association with a user account.

The marker authentication section 162 of the login controller 160detects, from the shot image, the image of a marker corresponding to theface region detected by the face authentication section 114.Specifically, the marker authentication section 162 detects the image ofthe marker that should exist at a relative position set in advance basedon the position coordinates of the face region provided from the faceauthentication section 114. At this time, like the above-described faceframe, a marker frame may be displayed at the position at which themarker should be held in the displayed image on the output device 4.Furthermore, the online ID of the identified user may be displayed nearthe marker frame.

In the shot image, the marker authentication section 162 makes a markersearch in a region that has a predetermined size and is in a presetpositional relationship with the face region provided from the faceauthentication section 114, such as a region on the chest. The markerauthentication section 162 then notifies the login processing section166 of color information of the detected marker in association with theinformation on the registered user notified from the face authenticationsection 114. When receiving this notification, the login processingsection 166 allows this user to log in to the information processingdevice 10 and notifies information relating to the correspondencebetween the registered user and the marker color to an execution mainentity (not shown) of information processing of a game or the like.Executing the same login processing for plural users allows theexecution main entity of the information processing to discriminate themotion of each user based on the color of the marker.

If a monocular camera is used as the camera 7 and a pair of face andmarker is detected from one shot image, the login processing iscompleted by the above-described configuration. On the other hand, aconsideration will be made about separately shooting an image used forface recognition and an image used for marker detection in order to keephigh accuracy in both the face recognition and the marker detection. Amarker having specific size, color, shape, luminance, and so forth iseasy to detect from room, person, object, etc. captured as an image andit is also easy to identify plural markers when the colors thereof aremade different from each other. However, differently from in seeing bythe human, how the marker is captured in an image greatly changesdepending on the shooting environment such as the ambient brightness,whether an object is present or absent, and the ambient color and theshooting condition such as the exposure time, the aperture value, andthe depth of focus.

In the case of shooting a wide-angle image including a user and a room,generally the shooting condition such as the white balance and theexposure time are automatically adjusted in matching with the shootingenvironment, which allows acquisition of an image that is well-balancedas a whole. However, in the case of detecting a marker in the image,changing the shooting condition according to the environment in thismanner leads to change in how the marker is captured, i.e. the color,size, shape, luminance, and so forth of the image, which possibly causesa trouble in the detection processing.

For example, in the case of using a marker that emits light, if theexposure time decided according to the brightness of the room is toolong, possibly the RGB values of the light emitting part of the markerare saturated and an image that is white irrespective of the color ofthe light emitter and has a blurry contour is obtained. Furthermore, ifthe marker moves at a comparatively high speed, possibly its imageblurs.

Therefore, possibly the position of the marker cannot be accuratelyacquired and the color cannot be discriminated. Therefore, a stereocamera is used as the camera 7. An image obtained under a standardshooting condition is shot by one camera and an image obtained under apredetermined shooting condition suitable for detection of the marker isshot by the other camera. The former is used by the face authenticationsection 114 for face authentication and is used for displaying on theoutput device 4 by the taken image display section 112. The latter isused by the marker authentication section 162 for marker detection.

In such a mode, the distance identifier 164 corrects the disparity inthe two images shot by the stereo camera so that the markercorresponding to a face can be accurately identified. FIG. 14 shows anexample of images shot when a stereo camera is used as the camera 7. Inthis case, the shot images are stereo images obtained by shooting thesame space by the stereo camera from left and right positions separatefrom each other by a predetermined distance. Of them, a first image 408a is shot under the standard condition and a second image 408 b is shotunder the condition suitable for marker detection.

That is, the first image 408 a is a general image for which the shootingcondition is automatically adjusted according to the environment in theshooting. The second image 408 b is an image shot with focus on themarker and with shorter exposure time and a shallower depth of focus(smaller aperture value) compared with the first image 408 a forexample. By performing shooting under such a condition, the second image408 b is obtained as an image in which the light emitter part of themarker is close to the actual one in color, shape, size, and luminancealthough the brightness is totally low and other objects blur. Onlyeither one of the exposure time and the aperture value may be changed asthe shooting condition for marker detection or another parameter may bechanged.

Although these images are obtained by simultaneously shooting the samesubject, a disparity D is generated because the point of sight isdifferent. First, the face authentication section 114 specifies a faceregion 410 by using the first image 408 a. In the first image 408 a, amarker search region 412 is located just under the face. Specifically,it is a region that has the same center axis as that of the face region410 in the horizontal direction (x-axis direction) and is separate fromthe face region 410 by a predetermined distance d in the verticaldirection (y-axis direction). In the example of FIG. 14, the distance dis the distance from the jaw to the chest.

However, when the marker authentication section 162 carries out markerdetection by using the second image 408 b, a marker search region 414 inthis image is offset in the horizontal direction (x-axis direction) bythe disparity D from the search region in the first image 408 a. Thedisparity D changes depending on the distance of the subject from thecamera. Therefore, the distance identifier 164 identifies this distanceand provides it to the marker authentication section 162. Based on this,the marker authentication section 162 first decides the marker searchregion 412 in the first image 408 a based on the position coordinates ofthe face region 410 supplied from the face authentication section 114and then shifts it in the x-axis direction by the disparity D to therebydecide the marker search region 414 in the second image 408 b. The shiftdirection differs depending on which of the left and right cameras isused to shoot the second image 408 b naturally.

FIG. 15 is a diagram adapted to explain the relationship between thedisparity in stereo images and the position of a subject in the depth′direction. Suppose that here the units of length are unified to themeter or the like unless stated. A first camera 7 a and a second camera7 b of the camera 7 are so set as to have parallel optical axespositioned across distance L. Suppose that the subject exists at aposition of the right-end arrow separate from these stereo cameras bydistance Z in the depth direction.

A width Δx in the actual space represented by one pixel of images shotby the respective cameras is proportional to the distance Z andexpressed as follows.

Δx=Z×w/W  (1)

In this expression, symbol W denotes the number of pixels of the camerasin the horizontal direction. Symbol w denotes the range of the field ofview of the actual space in the horizontal direction when the distance Zis 1. It is determined by the angle of sight.

The same subject shot by the cameras separate by the distance L has, onthe images thereof, the disparity D (pixels) in terms of the number ofpixels, expressed below substantially.

D=L/Δx=L×(W/w)×(1/Z)=C/Z  (2)

In this expression, symbol C is a value determined by the cameras andsetting thereof and can be regarded as a constant in operation. Themarker authentication section 162 acquires the distance Z from thedistance identifier 164 and obtains the disparity D on the images basedon the above-described expression (2) to decide a marker search regionin the second image 408 b. It will be understood by those skilled in theart that the above expression is one example and various calculationexpressions can be employed based on the principle of triangulation.

The disparity D of the marker search region is obtained from thedistance Z of the marker from the camera basically. Various methods arepossible as the method by which the distance identifier 164 identifiesthe distance Z. For example, a method is possible in which the firstimage 408 a and the second image 408 b are further utilized to generatea depth image by the stereo image method. The stereo image method is ageneral method in which feature points in stereo images are associatedand the position of a subject in the depth direction is calculated fromthe disparity of them. The depth image is an image in which the distanceof the subject from the camera in the depth direction is mapped ontwo-dimensional coordinates on the shot image plane and represented as apixel value.

However, given that the marker is held by a person, there is a limit tothe size of the marker. Therefore, generally the region of the image ofthe marker in a shot image is small. It is not easy to acquire thedistance from the camera with high accuracy based on such a smallregion. Therefore, by utilizing the fact that the marker and the facialsurface of a user who holds it are substantially equal in the distancefrom the camera, the disparity of the marker is derived with highaccuracy.

For example, if holding the input device 6 a in front of the chest asshown in FIG. 12 is prescribed as a pose at the time of login, themarker 402 is equivalent to the facial surface of the user in thedistance from the camera. Therefore, the disparity is obtained based onthe distance of the facial surface, which has a larger area than theregion of the image of the marker and thus is expected to allow highderivation accuracy.

Specifically, the distance identifier 164 reads out the pixel values ofthe face region detected by the face authentication section 114 in agenerated depth image. These pixel values represent the distance of thefacial surface from the camera and thus the distance Z is obtainedthrough e.g. calculation of the average of the whole region.

The above-described example has high effectiveness in that the distancecan be obtained with high accuracy without the need for new input databecause the stereo images originally shot are used. On the other hand,the distance identifier 164 may calculate the distance Z based on thesize of the face region without generating a depth image. Alternatively,the disparity of the face region in the stereo images may be substitutedfor the disparity of the marker. In e.g. a case in which the accuracy ofstereo matching and hence the accuracy of the depth image appear to beinsufficient due to e.g. difference in the shooting condition betweenthe first image 408 a and the second image 408 b, face recognitionprocessing may be executed for both the first image 408 a and the secondimage 408 b and thereby the face region of the same user may beidentified in both images to obtain the disparity.

The distance from the face to the chest, i.e. the distance d from theface region to the marker search region, may also be adjusted accordingto the distance from the camera to the face. Besides, the distanceidentifier 164 may use various existing techniques such as a techniqueof deriving the distance of the marker based on a time-of-flight (TOF)system by an infrared irradiation/detection system additionallyprovided.

Alternatively, it is also possible to employ a method in which thedistance Z is deemed as a fixed value and the user is made to recognizethe distance from the camera in advance and exist at the correspondingposition. If the relative positions of the facial surface and the markerin the depth direction are already, known, both do not necessarily needto exist at the same position because the distance of the marker can becalculated from the distance of the facial surface. For example, ifstretching the arms forward to dispose the marker on the foremost sideis employed as a pose at the time of login, the marker is located closerto the camera than the facial surface by the length of the arms andtherefore the disparity D of the marker can be derived from the distanceof the facial surface. Depending on the case, the image itself of themarker may be detected from the first image 408 a and the second image408 b and the disparity D of the marker may be directly identified.

In any case, by shooting an image under a condition separately set formarker detection and carrying out the marker detection in considerationof the disparity with the image used for face recognition, the accuracyof the marker detection can be kept irrespective of the illuminationenvironment and so forth at the time. Furthermore, for example whenplural users are close to each other, the possibility that the marker ofanother person is detected as confusion and login is disrupted can besuppressed. Moreover, the marker search region can be accuratelyobtained. Therefore, a uselessly-large region does not need to besearched, which can reduce the burden of marker detection processing.

Strictly, possibly the first camera 7 a and the second camera 7 binclude a slight amount of offset in the vertical direction, slightrotation of the imaging plane, and so forth as factors other than thedistance L in the horizontal direction depending on e.g. how lenses areattached. In this case, the offset of images between the first image 408a and the second image 408 b shot by both cameras includes componentsother than the disparity D in the horizontal direction. Therefore, themarker authentication section 162 may decide the marker search region414 in the second image 408 b in consideration of also these componentsin practice. Because individual differences also exist in the positionaloffset and rotational offset of the lenses, measurement is performed atthe time of manufacturing or the like and the measured values,parameters adapted to correct the offsets, and so forth are set insidethe information processing device 10.

FIG. 16 is a flowchart showing the procedure in which the informationprocessing device 10 executes login processing by carrying out faceauthentication and marker detection with use of stereo images. First,the face authentication section 114 reads out stereo images acquired bythe image acquirer 104 from the memory. Then, the face authenticationsection 114 extracts a part estimated to be a person's face in the firstimage shot under the standard condition, of these stereo images, andcompares it with face identification data held in the registered userinformation holder 168 to thereby determine that the extracted face isthe face of a registered user (S60). During the period in which a faceis not detected or the detected face is not the face of a registereduser, i.e. the face authentication is unsuccessful, the face detectionand the determination processing are repeated at a predetermined timeinterval (N of S60). If it is determined that the detected face is theface of a registered user and the face authentication succeeds (Y ofS60), the face authentication section 114 provides the markerauthentication section 162 with the position coordinates of the faceregion in the first image and the identification information of theuser.

Based on the position coordinates of the face region in the first image,the marker authentication section 162 decides a marker search region inthe second image for this user, i.e. in an image shot under thecondition for marker detection (S62). At this time, the distanceidentifier 164 reads out data of the stereo images acquired by the imageacquirer 104 and acquires the distance of the facial surface or a markerfrom the camera by stereo matching processing or the like to notify themarker authentication section 162 of the distance. This allows themarker authentication section 162 to decide the search region inconsideration of the disparity of the marker in these stereo images.Then, the marker authentication section 162 carries out marker detectionabout this search region (S64). If a marker is not detected for apredetermined time, the processing is ended with doing nothing (N ofS64).

If a marker is detected (Y of S64), the marker authentication section162 notifies the login processing section 166 of its color inassociation with the information on the registered user notified fromthe face authentication section 114. In response to this notification,the login processing section 166 allows this user to log in (S68). Atthis time, the login processing section 166 notifies an execution mainentity of a game or the like of information relating to thecorrespondence between the color and the registered user as describedabove.

Next, a consideration will be made about further enhancement in theaccuracy of the marker detection by the marker authentication section162 in S62. In the present embodiment, based on the color of a marker,the user who is operating the input device 6 having it is discriminated.Therefore, even when plural users who each hold the input device 6having a marker of a respective one of different colors aresimultaneously captured in a shot image, the correspondences between therespective colors and the positions of the users should be accuratelyderived irrespective of the positions.

However, particularly when the marker is a light emitter, possiblyvariation is caused in the color represented as the pixel value of theimage of the marker due to the color component included in light, thedetection accuracy of an imaging element such as a complementary metaloxide semiconductor (CMOS) sensor that detects it, the output accuracyof a correction circuit, and so forth. For example, when markers of fourcolors, blue, red, green, and pink, are used, a situation possiblyoccurs in which the component of pink strongly appears in the peripheryof the red marker. In this case, it is difficult to accurately determinewhether this marker is the red marker or the pink marker and whether thepink marker actually exists near the red marker. This occurs not only atthe time of login and is the same also in operation to a game or thelike after login. The determination error possibly causes erroneousoperation.

FIG. 17 schematically shows a shot image including the images ofmarkers. However, the images of users who hold them are omitted in thisdiagram. In a shot image 420, three input devices 422 a, 422 b, and 422c having the markers with colors different from each other are captured.Hatched circles near the markers of the input devices 422 a and 422 bschematically show regions where a color component different from theoriginal color of the marker strongly appears. For example, as shown inan enlarged image 424 of the marker part of the input device 422 a, apixel aggregate 426 representing a different color often appears near apixel aggregate 428 representing the color of the marker due to theabove-described reasons.

In such a case, in the region detected as a marker from the shot image,the part of the pixel aggregate 426 is not the image of the marker evenwhen having the marker color and therefore should be excluded from thedetection result. In the simplest idea, when plural colors closely existin this manner, the color of the largest area would be regarded as theoriginal color of the marker. However, the region occupied by the imageof the marker in the shot image is small as described above and possiblythe area itself that should be compared as above includes an error.Furthermore, as in the input devices 422 b and 422 c, markers whoseapparent size is different depending on the distance from the cameraappear to overlap with each other in some cases. Therefore, even anactual marker could be excluded.

Therefore, as a criterion of the exclusion, the size of the casingitself of the input device is added to the region area of each color.The color region to be excluded from the object detected as the markeris thereby identified with high accuracy. FIG. 18 is a flowchart showingthe procedure of processing of identifying the color that can be deemedas the marker in marker detection processing. This processing isexecuted by the marker authentication section 162 at the time of login.Besides, it can be executed also in operation of a game or the like.Therefore, the marker search region is diverse depending on thesituation of the processing. At the time of login, the marker searchregion may be a region in a predetermined positional relationship with aface region as described above. When moving the marker freely ispermitted in a game or the like, refinement of the search region may beadditionally performed by tracking processing or the like. Depending onthe case, the whole of the shot image may be deemed as the searchregion.

First, the marker authentication section 162 reads out a shot imageacquired by the image acquirer 104 from the memory and extracts a regionthat is possibly a region of the color of a marker through e.g. scanningof a search region in the shot image (S70). At this timing, pluralregions of the same color are extracted in some cases. Next, regionsformed of continuation of the same color or a color that can be deemedas the same color are sorted in decreasing order of area (S72). At thistime, each region is given an identification number i in increasingorder, i.e. 1, 2, 3, . . . . Next, the region of i=1, which is thelargest, is deemed as the n-th (=1st) target region (S74) and the rangecovered by the image of the casing of the input device when it isassumed that this region is the image of a marker is identified (S76).This range is, that is, a region inside the contour of the image of thecasing, specifically e.g. the black part of the input device 422 a inFIG. 17, and is decided based on the shape and size of the casing andthe distance of the input device from the camera.

The shape and size of the casing are already known naturally. Thedistance of the input device from the camera may be derived from thesize of the region i, or the distance identifier 164 may identify thedistance by shooting stereo images and creating a depth image. In thelatter case, in view of the possibility that the distance of the inputdevice itself includes many errors, the distance may be estimated fromthe distance of the body of the person who is holding it, such as theface or hand, as described above. Without generating a depth image, thedistance may be calculated based on the disparity of a marker or aperson's image in a pair of stereo images shot by the left and rightcameras. If at least part of a region of a color different from thecolor of the target region is included in the range of the image of therelevant casing, this region is excluded from the extraction result(S78).

When the number of all colors of the markers is defined as N, if thetarget region is not the N-th region (N of S80), the range covered bythe image of the casing is identified about the (n+1)-th target region,which has the next largest area. Then, if a region of a color differentfrom the color of the target region exists in this range of the image,this region is excluded from the extraction result (S82, S76, S78). Theprocessing of S82, S76, and S78 is repeated N times (N of S80) and theprocessing is ended if the exclusion processing for the N-th targetregion ends (Y of S80). If the number of regions extracted in S70 isequal to or smaller than N, the processing is ended after all regionsare employed as the target region. Due to this, only the regions thatare highly likely to be markers are left as the detection result.

Giving priority to the region with the larger area in this manner isbased on that this region is highly likely to be a marker and knowledgethat, if this region is assumed to be a marker and the range covered bythe image of the casing is assumed, a marker with a smaller image thanthe marker is not located on the camera side relative to this casing.This can prevent inconveniences that a different color componentaccidentally detected in the periphery of a marker as shown in FIG. 17is erroneously recognized as a marker and that any of plural markersclose to each other is erroneously excluded from the marker detectionsubject.

Instead of selecting the target region one by one sequentially from thelarger area as shown in FIG. 18, the following method may be employed.Specifically, about all extracted regions, scoring is performed based oncriteria such as the area of the region and whether or not the region iswithin the range covered by the image of the casing of a marker if aregion of a different color within a short distance is the marker.Furthermore, for each region, the possibility that the region is amarker is represented by a respective one of the scores. The finaldetection subject is thereby identified.

The present disclosure is described above based on the embodiment. Itwill be understood by those skilled in the art that this embodiment isexemplification and various modification examples are possible incombinations of the respective constituent elements and the respectiveprocessing processes thereof and such modification examples are alsowithin the scope of the present disclosure.

The present disclosure contains subject matter related to that disclosedin Japanese Priority Patent Application JP 2013-228136 filed in theJapan Patent Office on Nov. 1, 2013, the entire content of which ishereby incorporated by reference.

What is claimed is:
 1. An information processing device comprising: animage acquirer configured to acquire a shot image of a user; aregistered user information holder configured to hold faceidentification data of a registered user; a face recognition sectionconfigured to detect a face image of a registered user existing in theshot image by using face identification data held in the registered userinformation holder; and an information processing section configured toexecute information processing based on a detection result by the facerecognition section, wherein the face identification data includesinformation on a face image of a user shot in advance and anafter-processing image obtained by performing predetermined processingon the face image.
 2. The information processing device according toclaim 1, wherein the after-processing image includes an image obtainedby changing luminance of a predetermined region in the face image. 3.The information processing device according to claim 2, wherein theafter-processing image includes an image obtained by changing luminancebased on a range in which a shadow is made when a predetermined incidentangle of light is assumed.
 4. The information processing deviceaccording to claim 1, wherein the after-processing image includes animage obtained by making orientation of a face different fromorientation of the face in the face image.
 5. The information processingdevice according to claim 1, wherein the image acquirer acquires aplurality of shot images obtained by shooting a user from a plurality ofdirections, and the face identification data includes information onshot face images of the user in a plurality of orientations.
 6. Theinformation processing device according to claim 5, wherein theafter-processing image includes an image that is generated throughinterpolation from the face images of the user in the plurality oforientations and includes a face in an orientation different fromorientation of the face in the face image.
 7. The information processingdevice according to claim 1, wherein the after-processing image includesan image obtained by changing an expression of a face in the face image.8. The information processing device according to claim 1, wherein theafter-processing image includes an image obtained by combining the faceimage with another image representing a wearable object or hair.
 9. Theinformation processing device according to claim 1, wherein theafter-processing image includes an image obtained by changing color ofskin in the face image.
 10. An information processing method comprising:acquiring a shot image of a user from a connected imaging device;reading out face identification data of a registered user stored in astorage device and detecting a face image of a registered user existingin the shot image by using the face identification data; and executinginformation processing based on a result of the detection, wherein theface identification data includes information on a face image of a usershot in advance and an after-processing image obtained by performingpredetermined processing on the face image.
 11. A computer program for acomputer, comprising: acquiring a shot image of a user from a connectedimaging device; reading out face identification data of a registereduser stored in a storage device and detecting a face image of aregistered user existing in the shot image by using the faceidentification data; and executing information processing based on aresult of the detection, wherein the face identification data includesinformation on a face image of a user shot in advance and anafter-processing image obtained by performing predetermined processingon the face image.
 12. A computer-readable recording medium in which acomputer program is recorded, the computer program for a computerincluding: acquiring a shot image of a user from a connected imagingdevice; reading out face identification data of a registered user storedin a storage device and detecting a face image of a registered userexisting in the shot image by using the face identification data; andexecuting information processing based on a result of the detection,wherein the face identification data includes information on a faceimage of a user shot in advance and an after-processing image obtainedby performing predetermined processing on the face image.